The challenge of understanding biocomplexity in the environment requires sophisticated and creative approaches that integrate information across temporal and spatial scales, consider multiple levels of organization and cross-conceptual boundaries [Walker-Steffen97, Gell-Mann95]. Long-term data-collection for systematic and ecological field studies and continuous environmental monitoring are the domain of Biological Field Stations, and offer opportunities to establish cross-cutting and integrated investigations that facilitate studies of biocomplexity [Michener-et.al.98, Lohr-et.al.95]. Over the past two decades we have seen extraordinary developments in the field of remote sensing and automated data collection, resulting in dramatic increases in spatial, spectral and temporal resolution at a geometrically declining cost per unit area [Colwell98]. Multi-purpose data analysis and visualization software provides tools to study large and complex data sets. The Internet facilitates global data access, distributed data processing, collaborative studies, virtual proximity and tele-robotic operation.
Remote sensing from satellite and airborne sensors has proved to be a tremendous tool for studying ``large'' biodiversity (e.g. spatial complexity of dominant plant species). While many scientists and land managers attempt to study biodiversity using top down remote sensing tools, the fact is that the vast majority of the biodiversity, and resulting biocomplexity, within an ecosystem exists at very small scales, and is not readily observable with even the best airborne and satellite based sensors [Keitt-Milne97]. To get down to where the complexity is, so to speak, sensing and monitoring needs to become ground based [Hamilton92, Hamilton00]. Breakthroughs in VLSI digital signal processing, miniature sensors, low-power micro-controllers and wireless digital networks will make possible the development of cheap and nearly ubiquitous ground-based monitoring systems for outdoor field. Fresh opportunities afforded by these technologies allow us to rethink how Biological Field Stations can participate in the global effort to answer the big questions posed by biocomplexity.
Observation techniques involving cameras and microphones are in increasingly widespread use, however they involve small numbers of devices and require continuous human observation, greatly constraining their capabilities in natural environments. Unattended, heterogeneous sensors/actuators will enable a vast range of new habitat studies via continuous monitoring techniques. The data from such a network will need to be filtered and partially analyzed within the network e.g. seismic sensors could trigger data-intensive assets such as cameras. The proposed technology offers the chance for programmed observation, triggered response with specified patterns, and automatically recorded and reported responses. Such capabilities require the development of robust, adaptive techniques for coordinating across distributed and heterogeneous sensor/actuator nodes, many of which may be wireless and energy-limited.
Fundamental technological advances are needed to enable adaptive, programmable multi-modal networks to identify indicators of interest and use those to trigger analysis, correlation, and recording of events. Moreover, current techniques will not scale to very large numbers of wireless nodes and do not make effective use of multiple sensor modalities. To realize this goal we are developing and planning to deploy unique and innovative capabilities at the James Reserve in Southern California. Three, multi-node monitoring grids (25-100 nodes per grid) will be implemented for fixed view multimedia and environmental sensor data loggers (using wireless technologies and solar power, and ultimately capable of limited mobility, unique observation scales, proximity detection, and environmental ruggedness). We will develop and implement coordinated actuation to support experiments such as triggered emission and recording of acoustic signals from target species. Multiple perspective monitoring will be integrated through the addition of tower-based video cameras for coordinated hyper-stereoptical mapping (3D) of canopy topology and volume, monitoring of seasonal phenology of overstory tree species, and mid-ground level vegetation within the monitoring grids. Mobile nodes will also be integrated, such as an all-terrain robot for remote viewing, high resolution dimensional imaging, and ``gap filling data collection'' within each monitoring grid. In the long term we will incorporate tagged-animals into the system through the use of micro-RFID tags. All of these capabilities will require application of self-configuring and energy-conserving algorithms and protocols to achieve ad hoc, wireless system deployment and operation in uncontrollable environmental conditions.
This network will allow us to develop scalable techniques for non-destructive, multi-scale spatio-temporal sampling and biocomplexity data visualizations, thus enabling the rapid and low-cost mapping of new dynamic scales of species diversity, ecosystem structure, and environmental change. The facilities will provide on-site and Internet-based opportunities for graduate students and faculty to utilize these new tools, including training and research application consulting. This technology promises great opportunities in education and research alike.
In the following sections we describe two critical system building blocks needed to realize long-lived wireless sensor networks, and then present the details of our experimental platform.